In this web development project, we are going to use Node Js and develop a web scraper to collect information from a website. As part of this project, you will learn and work with Node Js to connect the frontend and backend. Backend deals with server-side development. Unlike the frontend, the backend works behind the screen. It focuses on the architecture of a website, databases, scripting, etc. Backend developers write code to create communication between browser and server. For backend development, they build applications using server-side languages like PHP, Python, Ruby, Java, etc. And tools like Oracle, SQL, to communicate with the server and display it in the front-end for the user.
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What is Node Js?
Node js is free and an open-source server environment that runs on various platforms like Linux, Mac OS, Windows, etc. It uses JavaScript to communicate with the server. With the help of Node Js, you can create a page with dynamic content and create, read, open, write, delete, and close files on the server. Node Js can collect form data and add, delete, modify data in the database.
Advantages of using Node Js for backend development
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Web Scraping project implementation
Web scraping is the process of automating the monotonous tasks of collecting information from websites. Web scraping can be used to collect prices from e-commerce websites, emails, or leads to train Machine Learning and AI models. Below are two major processes involved in web scraping:
To get started with the project you need Node Js and npm installed on your computer. Then install the following dependencies to develop the web scraper.
Now we are going to scrap the data from the Reddit website. Since reddit uses javascript to load the content using an HTTP request library like axios will not work. Thus Pupeepter is used to scrap pages that require javascript execution.
Create a file named reddit-scrapper.js file and add the required code. This code launches puppeteer and executes the Javascript on the page to collect the HTML content by navigating to the provided URL.
After this Cheerio is used to analyze and extract the required data from the HTML string.
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